Abstract: This paper describes an investigation of the generation of desired sea states in a numerical wave model. Bimodal sea states containing energetic swell components can be coastal hazards along coastlines exposed to large oceanic fetches. Investigating the effects of long-period bimodal seas requires large computational domains and increased running time to ensure the development of the desired sea state. Long computational runs can cause mass stability issues due to the Stokes drift and wave reflection, which in turn affect results through the variation of the water level. A numerical wave flume, NEWRANS, was used to investigate two wave generation methods: the wave paddle method, allowing for a smaller domain; and the internal mass source function method, providing an open boundary allowing reflected waves to leave the domain. The two wave generation methods were validated against experimental data by comparing the wave generation accuracy and the variance of mass in the model during simulations. Results show that the wave paddle method not only accurately generates the desired sea state but also provides a more stable simulation, in which mass fluctuation has less of an effect on the water depth during the long-duration simulations. As a result, it is suggested that the wave paddle method with active wave absorption is preferable to the internal wave maker option when investigating intermediate-depth long-period bimodal seas for long-duration simulations.
Abstract: In order to improve the accuracy of prediction when using the empirical orthogonal function (EOF) method, this paper describes a novel approach for two-dimensional (2D) EOF analysis based on extrapolating both the spatial and temporal EOF components for long-term prediction of coastal morphological changes. The approach was investigated with data obtained from a process-based numerical model, COAST2D, which was applied to an idealized study site with a group of shore-parallel breakwaters. The progressive behavior of the spatial and temporal EOF components, related to bathymetric changes over a training period, was demonstrated, and EOF components were extrapolated with combined linear and exponential functions for long-term prediction. The extrapolated EOF components were then used to reconstruct bathymetric changes. The comparison of the reconstructed bathymetric changes with the modeled results from the COAST2D model illustrates that the presented approach can be effective for long-term prediction of coastal morphological changes, and extrapolating both the spatial and temporal EOF components yields better results than extrapolating only the temporal EOF component.
Abstract: In this study the generalized extreme value (GEV) distribution function was used to assess nonstationarity in annual maximum wave heights for selected locations in the Greek Seas, both in the present and future climate. The available significant wave height data were divided into groups corresponding to the present period (1951 to 2000), a first future period (2001 to 2050), and a second future period (2051 to 2100). For each time period, the parameters of the GEV distribution were specified as functions of time-varying covariates and estimated using the conditional density network (CDN). For each location and selected time period, a total number of 29 linear and nonlinear models were fitted to the wave data, for a given combination of covariates. The covariates used in the GEV-CDN models consisted of wind fields resulting from the Regional Climate Model version 3 (RegCM3) developed by the International Center for Theoritical Physics (ICTP) with a spatial resolution of 10 km × 10 km, after being processed using principal component analysis (PCA). The results obtained from the best fitted models in the present and future periods for each location were compared, revealing different patterns of relationships between wind components and extreme wave height quantiles in different parts of the Greek Seas and different periods. The analysis demonstrates an increase of extreme wave heights in the first future period as compared with the present period, causing a significant threat to Greek coastal areas in the North Aegean Sea and the Ionian Sea.
Abstract: The southern coast of the Gulf of Maine in the United States is prone to flooding caused by nor’easters. A state-of-the-art fully-coupled model, the Simulating WAves Nearshore (SWAN) model with unstructured grids and the ADvanced CIRCulation (ADCIRC) model, was used to study the hydrodynamic response in the Gulf of Maine during the Patriot’s Day storm of 2007, a notable example of nor’easters in this area. The model predictions agree well with the observed tide-surges and waves during this storm event. Waves and circulation in the Gulf of Maine were analyzed. The Georges Bank plays an important role in dissipating wave energy through the bottom friction when waves propagate over the bank from offshore to the inner gulf due to its shallow bathymetry. Wave energy dissipation results in decreasing significant wave height (SWH) in the cross-bank direction and wave radiation stress gradient, which in turn induces changes in currents. While the tidal currents are dominant over the Georges Bank and in the Bay of Fundy, the residual currents generated by the meteorological forcing and waves are significant over the Georges Bank and in the coastal area and can reach 0.3 m/s and 0.2 m/s, respectively. In the vicinity of the coast, the longshore current generated by the surface wind stress and wave radiation stress acting parallel to the coastline is inversely proportional to the water depth and will eventually be limited by the bottom friction. The storm surge level reaches 0.8 m along the western periphery of the Gulf of Maine while the wave set-up due to radiation stress variation reaches 0.2 m. Therefore, it is significant to coastal flooding.
Abstract: In this study the medium-term response of beach profiles was investigated at two sites: a gently sloping sandy beach and a steeper mixed sand and gravel beach. The former is the Duck site in North Carolina, on the east coast of the USA, which is exposed to Atlantic Ocean swells and storm waves, and the latter is the Milford-on-Sea site at Christchurch Bay, on the south coast of England, which is partially sheltered from Atlantic swells but has a directionally bimodal wave exposure. The data sets comprise detailed bathymetric surveys of beach profiles covering a period of more than 25 years for the Duck site and over 18 years for the Milford-on-Sea site. The structure of the data sets and the data-driven methods are described. Canonical correlation analysis (CCA) was used to find linkages between the wave characteristics and beach profiles. The sensitivity of the linkages was investigated by deploying a wave height threshold to filter out the smaller waves incrementally. The results of the analysis indicate that, for the gently sloping sandy beach, waves of all heights are important to the morphological response. For the mixed sand and gravel beach, filtering the smaller waves improves the statistical fit and it suggests that low-height waves do not play a primary role in the medium-term morphological response, which is primarily driven by the intermittent larger storm waves.
Abstract: Accurately forecasting ocean waves during typhoon events is extremely important in aiding the mitigation and minimization of their potential damage to the coastal infrastructure, and the protection of coastal communities. However, due to the complex hydrological and meteorological interaction and uncertainties arising from different modeling systems, quantifying the uncertainties and improving the forecasting accuracy of modeled typhoon-induced waves remain challenging. This paper presents a practical approach to optimizing model-ensemble wave heights in an attempt to improve the accuracy of real-time typhoon wave forecasting. A locally weighted learning algorithm is used to obtain the weights for the wave heights computed by the WAVEWATCH III wave model driven by winds from four different weather models (model-ensembles). The optimized weights are subsequently used to calculate the resulting wave heights from the model-ensembles. The results show that the Optimization is capable of capturing the different behavioral effects of the different weather models on wave generation. Comparison with the measurements at the selected wave buoy locations shows that the optimized weights, obtained through a training process, can significantly improve the accuracy of the forecasted wave heights over the standard mean values, particularly for typhoon-induced peak waves. The results also indicate that the algorithm is easy to implement and practical for real-time wave forecasting.
Abstract: This paper presents a study on the improvement of wind field hindcasts for two typical tropical cyclones, i.e., Fanapi and Meranti, which occurred in 2010. The performance of the three existing models for the hindcasting of cyclone wind fields is first examined, and then two modification methods are proposed to improve the hindcasted results. The first one is the superposition method, which superposes the wind field calculated from the parametric cyclone model on that obtained from the Cross-Calibrated Multi-Platform (CCMP) reanalysis data. The radius used for the superposition is based on an analysis of the minimum difference between the two wind fields. The other one is the direct modification method, which directly modifies the CCMP reanalysis data according to the ratio of the measured maximum wind speed to the reanalyzed value as well as the distance from the cyclone center. Using these two methods, the problem of underestimation of strong winds in reanalysis data can be overcome. Both methods show considerable improvements in the hindcasting of tropical cyclone wind fields, compared with the cyclone wind model and the reanalysis data.
Abstract: Modal parameter identification is a core issue in health monitoring and damage detection for hydraulic structures. For a roof overflow hydropower station with a bulb tubular unit under ambient excitation, a complex unit-powerhouse-dam coupling vibration system increases the difficulties of modal parameter identification. In this study, in view of the difficulties of modal order determination and the noise jamming caused by ambient excitation, along with false mode identification and elimination problems, the ensemble empirical mode decomposition (EEMD) method was used to decrease noise, the singular entropy increment spectrum was used to determine system order, and multiple criteria were used to eliminate false modes. The eigensystem realization algorithm (ERA) and stochastic subspace identification (SSI) method were then used to identify modal parameters. The results show that the relative errors of frequencies in the first four modes were within 10% for the ERA method, while those of SSI were over 10% in the second and third modes. Therefore, the ERA method is more appropriate for identifying the structural modal parameters for this particular powerhouse layout.
Abstract: Prolonged immersion in floodwater is one of the main causes of embankment failure or dam breaks, although failure mechanisms have not been extensively studied. In this study, an embankment model was constructed to investigate the influence of prolonged immersion in floodwater on the failure of an embankment. The results indicate that: (1) the phreatic surface gradually rises and negative pore pressures gradually dissipate with the time of prolonged immersion in floodwater, and, finally, a stable and fully saturated state is reached; (2) observable cracks and a heave phenomenon are found near the downstream toe and in the top stratum of the foundation, which are attributed to the large uplift pressure on the interface between the top stratum and the pervious substratum, the tremendous impact effect induced by the rapid rise in water level, and the reduction of shear strength of heavy silt loam. The present study enhances our in-depth knowledge of the mechanisms of embankment failure induced by floodwater, and provides experimental data for validation of mathematical models of the embankment seepage failure.
